As wireless devices continue to become more prevalent, heterogeneous wireless networks - in which communicating devices have at their disposal multiple types of radios - will become the norm. Communication between nodes in these networks ought to be as simple as possible; they should be able to seamlessly switch between different radios and network stacks on the fly in order to better serve the user. To make this a possibility, we consider the challenging problems of when two communicating devices should decide to switch to a different radio, and which radio they should choose. We design an autonomous and intelligent radio switch (AIRS) decision algorithm that uses predicted radio availability and user profiles to choose the best available radio for two adjacent devices. The decision algorithm uses several parameters to avoid switching radios too frequently. We use a simulation study to evaluate the best settings for several parameters, then show that the AIRS system performs better than several alternative algorithms. AIRS is able to provide dynamic, but stable radio switching, while balancing the competing objectives of high throughput and low power consumption.

Communication between wireless devices ought to be as simple as possible; they should be able to seamlessly switch between different radios and network stacks on the fly in order to better serve the user. To make this a possibility, we consider the challenging problem of predicting link quality in a changing mobile environment. In this paper we present an algorithm that uses Weighted Least Squares Regression to predict whether a given link can meet application requirements in terms of throughput, delay, and jitter. We use a simulation study to demonstrate that our algorithm is able to predict link quality accurately and stably in a frequently changing mobile environment. The prediction algorithm is more accurate than several alternative algorithms, and the overhead caused by the link measurements is negligible in terms of throughput and power consumption.

In this paper we consider the problem of distinguishing whether frame loss at the MAC layer has occurred due to mobility or congestion. Most ad hoc routing protocols make the faulty assumption that all frame loss means the destination node has moved, resulting in significant overhead as they initiate the repair of routes that have not been broken. We design a mobility detection algorithm, MDA, that properly detects the cause of a lost frame, then coordinates with the routing protocol so that it reacts properly. This approach dramatically reduces routing protocol overhead and significantly increases application throughput. We use a simulation study to demonstrate the effectiveness of MDA and to determine the proper setting for MDA parameters.

Devices with multiple wireless interfaces are becoming increasingly popular. We envision that these devices will become the building block for future mesh networks, providing seamless connectivity across a range of heterogeneous devices. Although these devices typically implement frequency sharing, using either direct sequence spread spectrum (DSSS) or frequency hopping spread spectrum (FHSS), they may still interfere with one another. In this paper we provide a novel radio interference avoidance (RIA) algorithm that solves the problem of interference between IEEE 802.11 and Bluetooth. We then extend this algorithm to other types of DSSS and FHSS combinations. Though the algorithm is limited to devices with both of these interfaces, this is a very common case. We analytically derive the expected value of the response time for RIA and run simulations to demonstrate its effectiveness. Our results indicate that RIA is able to eliminate interference with a very short response time. RIA also outperforms adaptive frequency hopping, a solution proposed by the IEEE 802.15 co-existence working group.

Transport selection mechanisms are designed to facilitate seamless connectivity in heterogeneous multi-transport environments, allowing access to the "best" available transport according to user requirements. Evaluating transport configurations dynamically according to the user's preferences and quality of service (QoS) requirements is a challenging task. This paper describes a quantitative approach that applies the Utility Theorem and Nash's Bargaining solution to heterogeneous wireless environments. The mathematical model presented generates and adjusts the transport preference list dynamically depending on the degree to which a transport satisfies user preferences and the application's QoS requirements. We incorporate a negotiation engine using the axiomatic multi-transport bargaining algorithm to integrate local and remote users' requirements in a mutually beneficial manner as devices are connected via a peer-to-peer link. The transport selection model discussed in this paper is computationally light with modest communication overhead, making it suitable for mobile devices